The fluid infusion of musical culture: embodied experiences in a grade one classroom
Bibliographic record
Abstract
Children’s daily, embodied music experiences are integral to how children live and function in the world. Growing out of a line of work focusing on the interplay between elementary children’s daily experiences of music, both in- and out-of-school and the impact on elementary music education curriculum, this research is nested within the theoretical discourses of experience, children’s musical culture, and children’s agency. Building upon this work, findings from a two-phase, 6-month inquiry, situated in an urban, Canadian, Grade 1 French Immersion classroom, draw upon the tools of ethnography and narrative inquiry, with the intention of deepening understandings of how informal music-making and sound function in children’s lives. Phase one findings highlight: (1) the frequency and spontaneity of children’s daily music experiences, both in- and out-of-school, (2) the nature of how music and sound function fluidly in a variety of contexts as integral to children’s experience, and (3) the power of musical behaviours in assisting young children to acquire French vocabulary and literacy skills. Important considerations for teacher education include: the necessity of creating space in elementary curriculum to engage children in music-making, integrating and infusing the Arts fluidly across the curriculum, and encouraging children autonomy in their musical engagement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".